Fig. 3
From: Noncollapsibility and its role in quantifying confounding bias in logistic regression
The noncollapsibility effect (\({{\varvec{\beta}}}_{1}^{\boldsymbol{*}}-{{\varvec{\beta}}}_{1}^{\boldsymbol{^{\prime}}}\)) as a function of the confounder-outcome effect collapsed over all sample sizes. Panel A: each line represents a positive exposure-outcome effect. Panel B: each line represents a negative exposure-outcome effect